How To Apply Multiple Imputation In Propensity Score Matching With Partially Observed Confounders: A Simulation Study And Practical Recommendations,
2021
Stanford University
How To Apply Multiple Imputation In Propensity Score Matching With Partially Observed Confounders: A Simulation Study And Practical Recommendations, Albee Ling, Maria Montez-Rath, Maya Mathur, Kris Kapphahn, Manisha Desai
Journal of Modern Applied Statistical Methods
Propensity score matching (PSM) has been widely used to mitigate confounding in observational studies, although complications arise when the covariates used to estimate the PS are only partially observed. Multiple imputation (MI) is a potential solution for handling missing covariates in the estimation of the PS. However, it is not clear how to best apply MI strategies in the context of PSM. We conducted a simulation study to compare the performances of popular non-MI missing data methods and various MI-based strategies under different missing data mechanisms. We found that commonly applied missing data methods resulted in biased and inefficient estimates, …
A New Right-Skewed Upside Down Bathtub Shaped Heavy-Tailed Distribution And Its Applications,
2021
Central University of South Bihar, Gaya, India
A New Right-Skewed Upside Down Bathtub Shaped Heavy-Tailed Distribution And Its Applications, Sandeep Kumar Maurya, Sanjay K. Singh, Umesh Singh
Journal of Modern Applied Statistical Methods
A one parameter right skewed, upside down bathtub type, heavy-tailed distribution is derived. Various statistical properties and maximum likelihood approaches for estimation purpose are studied. Five different real data sets with four different models are considered to illustrate the suitability of the proposed model.
On The Level Of Precision Of A Heterogeneous Transfer Function In A Statistical Neural Network Model,
2021
University of Ibadan
On The Level Of Precision Of A Heterogeneous Transfer Function In A Statistical Neural Network Model, Christopher Godwin Udomboso
Journal of Modern Applied Statistical Methods
A heterogeneous function of the statistical neural network is presented from two transfer functions: symmetric saturated linear and hyperbolic tangent sigmoid. The precision of the derived heterogeneous model over their respective homogeneous forms are established, both at increased sample sizes hidden neurons. Results further show the sensitivity of the heterogeneous model to increase in hidden neurons.
A New Generalized Family Of Distributions For Lifetime Data,
2021
King Abdulaziz University
A New Generalized Family Of Distributions For Lifetime Data, Maha A. D. Aldahlan, Mohamed G. Khalil, Ahmed Z. Afify
Journal of Modern Applied Statistical Methods
A new class of continuous distributions called the generalized Burr X-G family is introduced. Some special models of the new family are provided. Some of its mathematical properties including explicit expressions for the quantile and generating functions, ordinary and incomplete moments, order statistics and Rényi entropy are derived. The maximum likelihood is used for estimating the model parameters. The flexibility of the generated family is illustrated by means of two applications to real data sets.
Jmasm 57: Bayesian Survival Analysis Of Lomax Family Models With Stan (R),
2021
Aligarh Muslim University
Jmasm 57: Bayesian Survival Analysis Of Lomax Family Models With Stan (R), Mohammed H. A. Abujarad, Athar Ali Khan
Journal of Modern Applied Statistical Methods
An attempt is made to fit three distributions, the Lomax, exponential Lomax, and Weibull Lomax to implement Bayesian methods to analyze Myeloma patients using Stan. This model is applied to a real survival censored data so that all the concepts and computations will be around the same data. A code was developed and improved to implement censored mechanism throughout using rstan. Furthermore, parallel simulation tools are also implemented with an extensive use of rstan.
Vif-Regression Screening Ultrahigh Dimensional Feature Space,
2021
University of Al-Qadisiyah
Vif-Regression Screening Ultrahigh Dimensional Feature Space, Hassan S. Uraibi
Journal of Modern Applied Statistical Methods
Iterative Sure Independent Screening (ISIS) was proposed for the problem of variable selection with ultrahigh dimensional feature space. Unfortunately, the ISIS method transforms the dimensionality of features from ultrahigh to ultra-low and may result in un-reliable inference when the number of important variables particularly is greater than the screening threshold. The proposed method has transformed the ultrahigh dimensionality of features to high dimension space in order to remedy of losing some information by ISIS method. The proposed method is compared with ISIS method by using real data and simulation. The results show this method is more efficient and more reliable …
A Simple Random Sampling Modified Dual To Product Estimator For Estimating Population Mean Using Order Statistics,
2021
Central University of Rajasthan
A Simple Random Sampling Modified Dual To Product Estimator For Estimating Population Mean Using Order Statistics, Sanjay Kumar, Priyanka Chhaparwal
Journal of Modern Applied Statistical Methods
Bandopadhyaya (1980) developed a dual to product estimator using robust modified maximum likelihood estimators (MMLE’s). Their properties were obtained theoretically and supported through simulations studies with generated as well as one real data set. Robustness properties in the presence of outliers and confidence intervals were studied.
Penalized Likelihood Estimation Of Gamma Distributed Response Variable Via Corrected Solution Of Regression Coefficients,
2021
University of lbadan, Nigeria
Penalized Likelihood Estimation Of Gamma Distributed Response Variable Via Corrected Solution Of Regression Coefficients, Rasaki Olawale Olanrewaju
Journal of Modern Applied Statistical Methods
A Gamma distributed response is subjected to regression penalized likelihood estimations of Least Absolute Shrinkage and Selection Operator (LASSO) and Minimax Concave Penalty via Generalized Linear Models (GLMs). The Gamma related disturbance controls the influence of skewness and spread in the corrected path solutions of the regression coefficients.
Inference For Step-Stress Partially Accelerated Life Test Model With An Adaptive Type-I Progressively Hybrid Censored Data,
2021
Saudi Electronic University Riyadh, Saudi Arabia
Inference For Step-Stress Partially Accelerated Life Test Model With An Adaptive Type-I Progressively Hybrid Censored Data, Showkat Ahmad Lone, Ahmadur Rahman, Tanveer A. Tarray
Journal of Modern Applied Statistical Methods
Consider estimating data of failure times under step-stress partially accelerated life tests based on adaptive Type-I hybrid censoring. The mathematical model related to the lifetime of the test units is assumed to follow Rayleigh distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameter and tampering coefficient. Also, the work is conducted under a traditional Type-I hybrid censoring plan (scheme). A Monte Carlo simulation algorithm is used to evaluate and compare the performances of the estimators of the tempering coefficient and model parameters under both progressively hybrid censoring plans. The comparison is carried out on the basis of …
Data-Driven Analytical Modeling Of Multiple Myeloma Cancer, U.S. Crop Production And Monitoring Process,
2021
University of South Florida
Data-Driven Analytical Modeling Of Multiple Myeloma Cancer, U.S. Crop Production And Monitoring Process, Lohuwa Mamudu
USF Tampa Graduate Theses and Dissertations
Globally, cancer disease is a major health issue causing a lot of deaths. The duration of time an individual diagnosed with a particular type of cancer survives has become a major area of research concern. The Kaplan Meier and Cox Proportional Hazard (Cox-PH) model have been a traditionally used method for survival analysis of cancer data. These techniques of cancer survival analysis are developed from nonparametric and semi-parametric approaches, respectively, which are not as robust as a parametric approach. In this dissertation, we proposed a new method of cancer survival analysis based on a parametric approach using multiple myeloma cancer …
Fully Bayesian Analysis Of Relevance Vector
Machine Classification With Probit Link Function
For Imbalanced Data Problem,
2021
Dalian Maritime University
Fully Bayesian Analysis Of Relevance Vector Machine Classification With Probit Link Function For Imbalanced Data Problem, Wenyang Wang, Dongchu Sun, Peng Shao, Haibo Kuang, Cong Sui
Department of Statistics: Faculty Publications
The original RVM classification model uses the logistic link function to build the likelihood function making the model hard to be conducted since the posterior of the weight parameter has no closed-form solution. This article proposes the probit link function approach instead of the logistic one for the likelihood function in the RVM classification model, namely PRVM (RVM with the probit link function). We show that the posterior of the weight parameter in PRVM follows the Multivariate Normal distribution and achieves a closed-form solution. A latent variable is needed in our algorithms to simplify the Bayesian computation greatly, and its …
Efficient, Positive, And Energy Stable Schemes For Multi-D Poisson–Nernst–Planck Systems,
2021
Missouri University of Science and Technology
Efficient, Positive, And Energy Stable Schemes For Multi-D Poisson–Nernst–Planck Systems, Hailiang Liu, Wumaier Maimaitiyiming
Mathematics and Statistics Faculty Research & Creative Works
In this paper, we design, analyze, and numerically validate positive and energy-dissipating schemes for solving the time-dependent multi-dimensional system of Poisson–Nernst–Planck equations, which has found much use in the modeling of biological membrane channels and semiconductor devices. The semi-implicit time discretization based on a reformulation of the system gives a well-posed elliptic system, which is shown to preserve solution positivity for arbitrary time steps. The first order (in time) fully discrete scheme is shown to preserve solution positivity and mass conservation unconditionally, and energy dissipation with only a mild O (1) time step restriction. The scheme is also shown to …
Weighted Geometric Mean And Its Properties,
2021
Oles Honchar Dnipro National University
Weighted Geometric Mean And Its Properties, Ievgen Turchyn
Applications and Applied Mathematics: An International Journal (AAM)
Various means (the arithmetic mean, the geometric mean, the harmonic mean, the power means) are often used as central tendency statistics. A new statistic of such type is offered for a sample from a distribution on the positive semi-axis, the γ-weighted geometric mean. This statistic is a certain weighted geometric mean with adaptive weights. Monte Carlo simulations showed that the γ-weighted geometric mean possesses low variance: smaller than the variance of the 0.20-trimmed mean for the Lomax distribution. The bias of the new statistic was also studied. We studied the bias in terms of nonparametric confidence intervals for the quantiles …
Analysis Of Means (Anom) Concepts And Computations,
2021
University of Houston – Clear Lake
Analysis Of Means (Anom) Concepts And Computations, Kalanka P. Jayalath, Jacob Turner
Applications and Applied Mathematics: An International Journal (AAM)
The classical Analysis of Means (ANOM) is a statistical inferencing procedure and visualization tool to analyze means from experiments with fixed effects. It can serve as an alternative to the Analysis of Variance (ANOVA) procedure that has distinct advantages when determining which effects contributed to an overall test’s significant result. ANOM has been extended to handle numerous situations including robust procedures involving ranks. More recent advancements of this procedure allow one to handle both random, and mixed effect models. In this work, we discuss the recent developments on ANOM methods that are useful in practice, provide examples that illustrate their …
Some Asymptotic Properties Of Conditional Density Function For Functional Data Under Random Censorship,
2021
University Djillali LIABES of Sidi Bel Abbes
Some Asymptotic Properties Of Conditional Density Function For Functional Data Under Random Censorship, Fatima Akkal, Abbes Rabhi, Latifa Keddani
Applications and Applied Mathematics: An International Journal (AAM)
In this work, we investigate the asymptotic properties of a nonparametric mode of a conditional density when the real response variable is censored and the explanatory variable is valued in a semi- metric space under ergodic data. First of all, we establish asymptotic properties for a conditional density estimator from which we derive an central limit theorem (CLT) of the conditional mode estimator. Simulation study is also presented to illustrate the validity and finite sample performance of the considered estimator.
A Geometric Approach To Conditioning And The Search For Minimum Variance Unbiased Estimators,
2021
Rochester Institute of Technology
A Geometric Approach To Conditioning And The Search For Minimum Variance Unbiased Estimators, David L. Farnsworth, James E. Marengo
Articles
Our purpose is twofold: to present a prototypical example of the conditioning technique to obtain the best estimator of a parameter and to show that this technique resides in the structure of an inner product space. The technique uses conditioning of an unbiased estimator on a sufficient statistic. This procedure is founded upon the conditional variance formula, which leads to an inner product space and a geometric interpretation. The example clearly illustrates the dependence on the sampling methodology. These advantages show the power and centrality of this process.
Pivot Points In Bivariate Linear Regression,
2021
Rochester Institute of Technology
Pivot Points In Bivariate Linear Regression, David L. Farnsworth, Carl V. Lutzer
Articles
There are little-noticed points in the plane, which are artifacts of linear regression. The points, which are called pivot points, are the intersections of sets of regression lines. We derive the coordinates of the pivot point and explain its sources. We show how a pivot point arises in a certain notable data set, which has been analyzed often for points of high leverage. We obtain the application of pivot points that shortens calculations when updating a set of bivariate observations by adding a new point.
Statistically Defensible Wind Tunnel Models,
2021
Air Force Institute of Technology
Statistically Defensible Wind Tunnel Models, Timothy A. Roche
Theses and Dissertations
Wind tunnels are used to test scale-model air frames in order to collect aerodynamic data. The Subsonic Aerodynamic Research Laboratory (SARL) Wind Tunnel is a low speed wind tunnel located at Wright-Patterson Air Force Base. The SARL Wind Tunnel team approached AFIT for assistance in creating statistically defensible models for the conditions inside the wind tunnel. During a wind tunnel test, pressure sensors cannot be placed at the test model. Instead, pressure is measured by a pitot probe permanently mounted in the corner of the test chamber. The pressure at the model location is predicted from the measurements taken by …
Nonparametric Relative Error Estimation Via Functional Regressor By The K Nearest Neighbors Smoothing Under Truncation Random Data,
2021
Djillali Liabes University
Nonparametric Relative Error Estimation Via Functional Regressor By The K Nearest Neighbors Smoothing Under Truncation Random Data, Wahiba Bouabsa
Applications and Applied Mathematics: An International Journal (AAM)
The relation between a functional random covariate and a scalar answer due to left truncation by a different random variable is evaluated in this study with the kNN method. In particular, in order to produce a nonparametric kNN regression operator of these functional truncated data as a loss function, we should use mean squared relative error. In number of neighbors, we establish an estimator and assess the uniform consistency performance with the convergence rate. Then, for different levels of computational truncated data, a simulation analysis was carried out on finite-sized samples to show the feasibility of our estimation procedure and …
Theoretical Study Of Mach Number And Compressibility Effect On The Slender Airfoils,
2021
Military Institute of Science and Technology
Theoretical Study Of Mach Number And Compressibility Effect On The Slender Airfoils, Abrar Hoque, Masudar Rahman, Ashabul Hoque
Applications and Applied Mathematics: An International Journal (AAM)
Theoretical development of the velocity potential equation for compressible flow and its various consequences has been presented. The geometrical interpretation of potential equation and conformal mapping technique are discussed where the mappings link the flow around a circular cylinder of a slender airfoil. The lift and drag coefficients are determined for the slender airfoils based on the Mach number and compressibility effects. The calculated lift coefficients show that with the increasing of attack angle it increases linearly and a higher lift coefficient is found for a smaller Mach number for any certain attack angle. Similarly, the drag profiles are determined …
